This notebook contains a set of analyses for analyzing ZeeGarcia boardgamegeek collection. The bulk of the analysis is focused on building a user-specific predictive model to predict the games that the specified user is likely to own. This enables us to ask questions like, based on the games the user currently owns, what games are a good fit for their collection? What upcoming games are they likely to purchase?
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We can look at a basic description of the number of games that the user owns, has rated, has previously owned, etc.
What years has the user owned/rated games from? While we can’t see when a user added or removed a game from their collection, we can look at their collection by the years in which their games were published.
We can look at the most frequent types of categories, mechanics, designers, and artists that appear in a user’s collection.
We’ll examine a predictive model trained on a user’s collection for games published through 2020. How many games has the user owned/rated/played in the training set (games prior to 2020)?
username | dataset | period | games_owned | games_rated |
ZeeGarcia | training | published before 2020 | 1,512 | 1,904 |
ZeeGarcia | validation | published 2020 | 55 | 81 |
ZeeGarcia | test | published after 2020 | 52 | 48 |
The main outcome we will be modeling for the user is owned, which refers to whether the user currently owns or has a previously owned a game in their collection. Our goal is to train a predictive model to learn the probability that a user will add a game to their collection based on its observable features.
We can examine coefficients from the model we trained, which is a logistic regression with elastic net regularization (which I will refer to as a penalized logistic regression). Positive values indicate that a feature increases a user’s probability of owning/rating a game, while negative values indicate a feature decreases the probability. To be precise, the coefficients indicate the effect of a particular feature on the log-odds of a user owning a game.
Why did the model identify these features? We can make density plots of the important features for predicting whether the user owned a game. Blue indicates the density for games owned by the user, while grey indicates the density for games not owned by the user.
Binary predictors can be difficult to see with this visualization, so we can also directly examine the percentage of games in a user’s collection with a predictor vs the percentage of all games with that predictor.
% of Games with Feature | ||||
username | Feature | In_Collection | All_Games | Ratio |
ZeeGarcia | Artist Vincent Dutrait | 2.5% | 0.2% | 12.26 |
ZeeGarcia | Mechanism Tableau Building | 4.2% | 0.8% | 5.51 |
ZeeGarcia | ZMan Games | 6.7% | 1.9% | 3.56 |
ZeeGarcia | Tricktaking | 4.3% | 1.2% | 3.52 |
ZeeGarcia | Renegade Game Studios | 1.7% | 0.5% | 3.42 |
ZeeGarcia | Iello | 5.6% | 1.7% | 3.30 |
ZeeGarcia | Asmodee | 9.8% | 3.3% | 2.97 |
ZeeGarcia | Rio Grande Games | 7.5% | 2.7% | 2.80 |
ZeeGarcia | Fantasy Flight Games | 4.4% | 1.7% | 2.57 |
ZeeGarcia | Pegasus Spiele | 7.2% | 3.0% | 2.40 |
ZeeGarcia | Open Drafting | 19.4% | 8.6% | 2.25 |
ZeeGarcia | Set Collection | 28.8% | 13.8% | 2.08 |
ZeeGarcia | Combinatorial | 3.0% | 1.6% | 1.85 |
ZeeGarcia | Hand Management | 39.3% | 22.0% | 1.78 |
ZeeGarcia | Card Game | 45.7% | 28.4% | 1.61 |
ZeeGarcia | Has Miniatures | 4.5% | 2.9% | 1.54 |
ZeeGarcia | Paper And Pencil | 3.5% | 2.3% | 1.51 |
ZeeGarcia | Games With Solitaire Rules | 10.1% | 7.0% | 1.45 |
ZeeGarcia | Parker Brothers | 2.3% | 2.9% | 0.80 |
ZeeGarcia | Miniatures Game | 2.4% | 5.7% | 0.42 |
ZeeGarcia | Action Dexterity | 1.5% | 5.3% | 0.29 |
ZeeGarcia | Steve Jackson Games | 0.3% | 1.0% | 0.26 |
ZeeGarcia | Childrens Game | 1.8% | 7.1% | 0.25 |
ZeeGarcia | Wargame | 1.3% | 17.2% | 0.08 |
ZeeGarcia | Simulation | 0.7% | 10.2% | 0.07 |
Before predicting games in upcoming years, we can examine how well the model did and what games it liked in the training set. In this case, we used resampling techniques (cross validation) to ensure that the model had not seen a game before making its predictions.
An easy way to examine the performance of classification model is to view a separation plot. We plot the predicted probabilities from the model for every game (from resampling) from lowest to highest. We then overlay a blue line for any game that the user does own. A good classifier is one that is able to separate the blue (games owned by the user) from the white (games not owned by the user), with most of the blue occurring at the highest probabilities (right side of the chart).
We can display this information in table form, displaying the 100 games with the highest probability of ownership, adding a blue line when the user does own the game.
Rank | Published | ID | Name | Pr(Owned) | Owned |
1 | 2015 | 177639 | Raptor | 0.999 | yes |
2 | 2005 | 15062 | Shadows over Camelot | 0.998 | yes |
3 | 2008 | 33107 | Senji | 0.996 | yes |
4 | 2016 | 200147 | Kanagawa | 0.995 | yes |
5 | 2019 | 265285 | Queenz: To Bee or Not to Bee | 0.994 | yes |
6 | 2012 | 129904 | Shadows over Camelot: The Card Game | 0.993 | no |
7 | 2011 | 103686 | Mundus Novus | 0.991 | yes |
8 | 2014 | 154443 | Madame Ching | 0.990 | yes |
9 | 2015 | 173346 | 7 Wonders Duel | 0.990 | yes |
10 | 2003 | 6068 | Queen's Necklace | 0.989 | yes |
11 | 2019 | 244191 | Naga Raja | 0.984 | yes |
12 | 2015 | 176920 | Mission: Red Planet (Second Edition) | 0.983 | yes |
13 | 2009 | 54998 | Cyclades | 0.980 | yes |
14 | 2014 | 155987 | Abyss | 0.976 | yes |
15 | 2016 | 194523 | HMS Dolores | 0.971 | no |
16 | 2009 | 40793 | Dice Town | 0.970 | yes |
17 | 2006 | 22141 | Cleopatra and the Society of Architects | 0.970 | yes |
18 | 2019 | 276042 | Conspiracy: Abyss Universe | 0.968 | yes |
19 | 2014 | 161138 | Dragon Run | 0.968 | yes |
20 | 2005 | 18258 | Mission: Red Planet | 0.967 | yes |
21 | 2000 | 478 | Citadels | 0.967 | yes |
22 | 2016 | 205610 | A Game of Thrones: Hand of the King | 0.966 | yes |
23 | 2007 | 29030 | Chicago Poker | 0.965 | yes |
24 | 2014 | 154203 | Imperial Settlers | 0.961 | yes |
25 | 2004 | 10997 | Boomtown | 0.959 | yes |
26 | 2012 | 116858 | Noah | 0.958 | yes |
27 | 2001 | 878 | Wyatt Earp | 0.958 | yes |
28 | 2010 | 65907 | Mystery Express | 0.952 | no |
29 | 2013 | 148290 | Longhorn | 0.951 | yes |
30 | 2016 | 190639 | Zany Penguins | 0.950 | yes |
31 | 2018 | 239840 | Micropolis | 0.949 | yes |
32 | 2013 | 134453 | The Little Prince: Make Me a Planet | 0.947 | yes |
33 | 2015 | 163968 | Elysium | 0.946 | yes |
34 | 2014 | 148228 | Splendor | 0.944 | yes |
35 | 2019 | 280501 | Three-Dragon Ante: Legendary Edition | 0.943 | yes |
36 | 2012 | 121921 | Robinson Crusoe: Adventures on the Cursed Island | 0.940 | yes |
37 | 2006 | 21763 | Mr. Jack | 0.940 | yes |
38 | 2004 | 9216 | Goa | 0.939 | yes |
39 | 2019 | 265031 | Ice Team | 0.938 | no |
40 | 2016 | 205398 | Citadels | 0.934 | yes |
41 | 1999 | 50 | Lost Cities | 0.932 | yes |
42 | 2018 | 199792 | Everdell | 0.931 | yes |
43 | 2017 | 197178 | DIG | 0.931 | yes |
44 | 2009 | 54043 | Jaipur | 0.930 | yes |
45 | 2013 | 143157 | SOS Titanic | 0.930 | yes |
46 | 2019 | 281960 | Kingdomino Duel | 0.928 | yes |
47 | 2006 | 24845 | Tomahawk | 0.925 | yes |
48 | 2007 | 28023 | Jamaica | 0.924 | yes |
49 | 2002 | 4471 | Fist of Dragonstones | 0.924 | yes |
50 | 2009 | 55427 | Mr. Jack in New York | 0.921 | yes |
51 | 2011 | 108783 | Dr. Shark | 0.921 | no |
52 | 2014 | 157354 | Five Tribes | 0.920 | yes |
53 | 2018 | 244330 | Scarabya | 0.915 | yes |
54 | 2016 | 197893 | Crazy Mistigri | 0.915 | no |
55 | 2010 | 67185 | Sobek | 0.914 | yes |
56 | 2016 | 191300 | Archaeology: The New Expedition | 0.909 | yes |
57 | 2013 | 145027 | Pentos | 0.905 | yes |
58 | 2017 | 192827 | RUM | 0.904 | yes |
59 | 2016 | 182120 | Histrio | 0.901 | yes |
60 | 2019 | 270836 | Imperial Settlers: Roll & Write | 0.900 | no |
61 | 2014 | 165662 | Haru Ichiban | 0.898 | yes |
62 | 1995 | 46 | Medici | 0.894 | no |
63 | 2018 | 250878 | Rebel Nox | 0.894 | no |
64 | 2018 | 260428 | Pandemic: Fall of Rome | 0.889 | yes |
65 | 2004 | 9509 | Iglu Iglu | 0.888 | yes |
66 | 2016 | 193210 | Dice Stars | 0.888 | yes |
67 | 1995 | 112 | Condottiere | 0.884 | yes |
68 | 2011 | 100423 | Elder Sign | 0.884 | yes |
69 | 2019 | 286096 | Tapestry | 0.883 | no |
70 | 2016 | 201920 | Pocket Madness | 0.882 | yes |
71 | 2013 | 137297 | Rise of Augustus | 0.880 | yes |
72 | 2018 | 241164 | Jurassic Snack | 0.876 | yes |
73 | 2012 | 125311 | Okiya | 0.875 | yes |
74 | 2006 | 28025 | Wicked Witches Way | 0.874 | yes |
75 | 2014 | 168609 | Artifacts, Inc. | 0.872 | yes |
76 | 2018 | 246742 | Château Aventure | 0.867 | no |
77 | 2004 | 14781 | Drôles de Zèbres | 0.864 | yes |
78 | 2019 | 270844 | Imperial Settlers: Empires of the North | 0.862 | yes |
79 | 2013 | 143693 | Glass Road | 0.862 | no |
80 | 2005 | 15880 | The Hollywood! Card Game | 0.861 | no |
81 | 2015 | 161383 | LIE | 0.857 | yes |
82 | 2019 | 266192 | Wingspan | 0.855 | yes |
83 | 2004 | 10682 | Atlas & Zeus | 0.855 | yes |
84 | 2010 | 68448 | 7 Wonders | 0.853 | yes |
85 | 2006 | 27117 | Animalia | 0.852 | yes |
86 | 2019 | 285774 | Marvel Champions: The Card Game | 0.849 | yes |
87 | 2019 | 283863 | The Magnificent | 0.849 | no |
88 | 2019 | 271088 | Ishtar: Gardens of Babylon | 0.848 | yes |
89 | 2017 | 232043 | Queendomino | 0.846 | yes |
90 | 2019 | 285984 | Last Bastion | 0.843 | yes |
91 | 2017 | 200847 | Secrets | 0.842 | no |
92 | 2010 | 72287 | Mr. Jack Pocket | 0.841 | yes |
93 | 2018 | 251890 | Gunkimono | 0.839 | no |
94 | 2013 | 125924 | Clubs | 0.838 | yes |
95 | 2018 | 255674 | Imhotep: The Duel | 0.837 | no |
96 | 2009 | 45134 | Arcana | 0.835 | yes |
97 | 2013 | 140620 | Lewis & Clark: The Expedition | 0.835 | yes |
98 | 2017 | 222885 | WOO | 0.833 | no |
99 | 2008 | 38054 | Snow Tails | 0.828 | yes |
100 | 2015 | 158915 | GEM | 0.823 | yes |
We can also more formally assess how well the model did in resampling by looking at the area under the receiver operating characteristic. A perfect model would receive a score of 1, while a model that cannot predict the outcome will default to a score of 0.5. The extent to which something is a good score depends on the setting, but generally anything in the .8 to .9 range is very good while the .7 to .8 range is perfectly acceptable.
Another way to think about the model performance is to view its lift, or its ability to detect the positive outcomes over that of a null model. High lift indicates the model can much more quickly find all of the positive outcomes (in this case, games owned or played by the user), while a model with no lift is no better than random guessing. A gains chart is another way to view this.
Finally, we can understand the performance of the model by examining its calibration. If the model assigns a probability of 5%, how often does the outcome actually occur? A well calibrated model is one in which the predicted probabilities reflect the probabilities we would observe in the actual data. We can assess the calibration of a model by grouping its predictions into bins and assessing how often we observe the outcome versus how often our model expects to observe the outcome.
A model that is well calibrated will closely follow the dashed line - its expected probabilities match that of the observed probabilities. A model that consistently underestimates the probability of the event will be over this dashed line, be a while a model that overestimates the probability will be under the dashed line.
What games does the model think ZeeGarcia is most likely to own that are not in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2012 | 129904 | Shadows over Camelot: The Card Game | 0.993 | no |
2016 | 194523 | HMS Dolores | 0.971 | no |
2010 | 65907 | Mystery Express | 0.952 | no |
2019 | 265031 | Ice Team | 0.938 | no |
2011 | 108783 | Dr. Shark | 0.921 | no |
What games does the model think ZeeGarcia is least likely to own that are in their collection?
Published | ID | Name | Pr(Owned) | Owned |
2014 | 165401 | Wir sind das Volk! | 0.007 | yes |
2007 | 28843 | 300: The Board Game | 0.008 | yes |
400 | 2136 | Pachisi | 0.011 | yes |
2012 | 123228 | Bling Bling Gemstone | 0.012 | yes |
2003 | 6351 | Gulo Gulo | 0.013 | yes |
Top 25 games most likely to be owned by the user in each year, highlighting in blue the games that the user has owned.
rank | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | 2019 |
1 | Shadows over Camelot: The Card Game | Longhorn | Madame Ching | Raptor | Kanagawa | DIG | Micropolis | Queenz: To Bee or Not to Bee |
2 | Noah | The Little Prince: Make Me a Planet | Abyss | 7 Wonders Duel | HMS Dolores | RUM | Everdell | Naga Raja |
3 | Robinson Crusoe: Adventures on the Cursed Island | SOS Titanic | Dragon Run | Mission: Red Planet (Second Edition) | A Game of Thrones: Hand of the King | Queendomino | Scarabya | Conspiracy: Abyss Universe |
4 | Okiya | Pentos | Imperial Settlers | Elysium | Zany Penguins | Secrets | Rebel Nox | Three-Dragon Ante: Legendary Edition |
5 | Targi | Rise of Augustus | Splendor | LIE | Citadels | WOO | Pandemic: Fall of Rome | Ice Team |
6 | Button Up! | Glass Road | Five Tribes | GEM | Crazy Mistigri | Oliver Twist | Jurassic Snack | Kingdomino Duel |
7 | Android: Netrunner | Clubs | Haru Ichiban | Pandemic Legacy: Season 1 | Archaeology: The New Expedition | Yamataï | Château Aventure | Imperial Settlers: Roll & Write |
8 | Zooloretto: The Dice Game | Lewis & Clark: The Expedition | Artifacts, Inc. | SHH | Histrio | BOO | Gunkimono | Tapestry |
9 | Think Again! | Bruges | Desperados of Dice Town | Arboretum | Dice Stars | ORC | Imhotep: The Duel | Imperial Settlers: Empires of the North |
10 | Eight-Minute Empire | Pathfinder Adventure Card Game: Rise of the Runelords – Base Set | Roll for the Galaxy | HUE | Pocket Madness | GYM | Treasure Island | Wingspan |
11 | Sky Tango | Le Fantôme de l'Opéra | Pandemic: The Cure | Oh My Goods! | Kingdomino | Pandemic Legacy: Season 2 | Imaginarium | Marvel Champions: The Card Game |
12 | Ginkgopolis | Legacy: The Testament of Duke de Crecy | Onirim (Second Edition) | Plums | 51st State: Master Set | A Column of Fire | Gizmos | The Magnificent |
13 | The Hobbit Card Game | Sushi Go! | Roll Through the Ages: The Iron Age | Mysterium | The Pyramid's Deadline | LYNGK | Penny Papers Adventures: The Valley of Wiraqocha | Ishtar: Gardens of Babylon |
14 | Divinare | Eight-Minute Empire: Legends | Chimera | Sylvion | Pandemic: Iberia | Nut | KeyForge: Call of the Archons | Last Bastion |
15 | Pirates of the Spanish Main: Shuffling the Deck | Room 25 | Diamonds: Second Edition | The Little Prince: Rising to the Stars | Pandemic: Reign of Cthulhu | Santa Maria | Duelosaur Island | Silver & Gold |
16 | New Amsterdam | Kobayakawa | Linko! | Holmes: Sherlock & Mycroft | Bloodborne: The Card Game | Ex Libris | Arkham Horror (Third Edition) | Unmatched: Robin Hood vs. Bigfoot |
17 | Seasons | The Phantom Society | La Isla | Dale of Merchants | The Castles of Burgundy: The Card Game | Jump Drive | Newton | Era: Medieval Age |
18 | Terra Mystica | UGO! | Viceroy | Warehouse 51 | Oceanos | Miaui | Penny Papers Adventures: The Temple of Apikhabou | It's a Wonderful World |
19 | Rent a Hero | Asante | Saboteur: The Duel | A Game of Gnomes | Backyard Builders Treehouse | Lovecraft Letter | Greedy Kingdoms | Tiny Towns |
20 | Neuroshima: Convoy | Mascarade | Sheriff of Nottingham | Bad Bunnies | Argo | The Fox in the Forest | Solenia | Amul |
21 | Uchronia | Mush! Mush!: Snow Tails 2 | Maskmen | Empires: Age of Discovery | Noxford | BOX | Underwater Cities | The Crew: The Quest for Planet Nine |
22 | Rumble in the Dungeon | Cinque Terre | Noble Treachery: The Last Alliance | 3 sind eine zu viel! | Medici: The Card Game | The Quest for El Dorado | The Pirate Republic | Res Arcana |
23 | Santa Cruz | Gravwell: Escape from the 9th Dimension | Yardmaster Express | Tales & Games: The Grasshopper & the Ant | Broom Service: The Card Game | SPY | Fist of Dragonstones: The Tavern Edition | Unmatched: Battle of Legends, Volume One |
24 | Android: Infiltration | Ghooost! | DungeonQuest Revised Edition | TKO | Star Wars: Destiny | Zooloretto Duell | Magic Fold | KeyForge: Age of Ascension |
25 | Libertalia | Cappuccino | Qwixx Card Game | Dead Man's Draw | Welcome Back to the Dungeon | SOW | Don't Mess with Cthulhu Deluxe | The Ancient World (Second Edition) |
Interactive table for predictions from resampling.
We’ll validate the model by looking at its predictions for games published in 2020. That is, how well did a model trained on a user’s collection through 2020 perform in predicting games for the user in 2020?
username | outcome | dataset | method | .metric | .estimate |
ZeeGarcia | owned | validation | glmnet | roc_auc | 0.734 |
Table of top 50 games from 2020, highlighting games that the user owns.
Published | ID | Name | Pr(Owned) | Owned |
2020 | 323262 | Velonimo | 0.951 | yes |
2020 | 297661 | Gold River | 0.935 | yes |
2020 | 265784 | Cleopatra and the Society of Architects: Deluxe Edition | 0.925 | yes |
2020 | 229782 | Roland Wright: The Dice Game | 0.902 | no |
2020 | 316377 | 7 Wonders (Second Edition) | 0.889 | yes |
2020 | 292917 | Mosquito Show | 0.868 | no |
2020 | 297666 | Jurassic Brunch | 0.858 | yes |
2020 | 293556 | Gloomy Graves | 0.791 | no |
2020 | 325635 | Unmatched: Little Red Riding Hood vs. Beowulf | 0.781 | no |
2020 | 300010 | Dragomino | 0.776 | no |
2020 | 303672 | Trek 12: Himalaya | 0.766 | yes |
2020 | 288169 | The Fox in the Forest Duet | 0.745 | no |
2020 | 314040 | Pandemic Legacy: Season 0 | 0.735 | yes |
2020 | 294484 | Unmatched: Cobble & Fog | 0.728 | no |
2020 | 291511 | Medici: The Dice Game | 0.716 | no |
2020 | 313531 | Rustling Leaves | 0.671 | no |
2020 | 301919 | Pandemic: Hot Zone – North America | 0.663 | yes |
2020 | 285071 | Ugly Christmas Sweaters | 0.663 | no |
2020 | 232414 | Oceans | 0.640 | yes |
2020 | 298572 | Cosmic Encounter Duel | 0.625 | no |
2020 | 245659 | Vampire: The Masquerade – Vendetta | 0.622 | no |
2020 | 293678 | Stellar | 0.604 | no |
2020 | 293309 | Kraken Attack! | 0.599 | no |
2020 | 256509 | The One Hundred Torii | 0.557 | no |
2020 | 270109 | Iwari | 0.555 | yes |
2020 | 295957 | Holi: Festival of Colors | 0.549 | no |
2020 | 299607 | Capital Lux 2: Generations | 0.512 | no |
2020 | 303054 | Yacht Rock | 0.509 | no |
2020 | 299169 | Spicy | 0.509 | no |
2020 | 304285 | Infinity Gauntlet: A Love Letter Game | 0.501 | yes |
2020 | 301399 | Lyttle Wood | 0.493 | yes |
2020 | 293296 | Splendor: Marvel | 0.483 | no |
2020 | 245658 | Unicorn Fever | 0.476 | no |
2020 | 301607 | KeyForge: Mass Mutation | 0.455 | no |
2020 | 298376 | MEOW | 0.447 | no |
2020 | 300930 | Schotten Totten 2 | 0.443 | no |
2020 | 324345 | キャットインザボックス (Cat in the box) | 0.439 | no |
2020 | 298047 | Marvel United | 0.435 | yes |
2020 | 296667 | Vintage | 0.434 | no |
2020 | 291457 | Gloomhaven: Jaws of the Lion | 0.433 | yes |
2020 | 298371 | Wild Space | 0.433 | no |
2020 | 300936 | Via Magica | 0.425 | no |
2020 | 295949 | Adventure Games: The Grand Hotel Abaddon | 0.416 | no |
2020 | 298065 | Santa Monica | 0.411 | no |
2020 | 284777 | Unmatched: Jurassic Park – InGen vs Raptors | 0.404 | no |
2020 | 283155 | Calico | 0.402 | no |
2020 | 309862 | Gudetama: The Tricky Egg Card Game | 0.400 | no |
2020 | 299592 | Beez | 0.398 | no |
2020 | 309113 | Ticket to Ride: Amsterdam | 0.398 | no |
2020 | 296512 | The Game: Quick & Easy | 0.390 | yes |
We can then refit our model to the training and validation set in order to predict all upcoming games for the user.
Examine the top 50 games for upcoming games, highlighting in blue ones the user already.
Published | ID | Name | Pr(Owned) | Owned |
2021 | 332944 | Sobek: 2 Players | 0.947 | yes |
2021 | 344415 | Trek 12: Amazonia | 0.854 | no |
2021 | 340041 | Kingdomino Origins | 0.843 | yes |
2021 | 329670 | Pandemic: Hot Zone – Europe | 0.822 | no |
2021 | 341358 | INSERT | 0.818 | no |
2021 | 334644 | Nicodemus | 0.778 | yes |
2021 | 333280 | Plata | 0.758 | no |
2021 | 329714 | Dreadful Circus | 0.735 | no |
2021 | 303676 | Oh My Brain | 0.726 | yes |
2022 | 295374 | Long Shot: The Dice Game | 0.667 | yes |
2022 | 349067 | The Lord of the Rings: The Card Game – Revised Core Set | 0.664 | no |
2021 | 295607 | Canopy | 0.610 | yes |
2021 | 310031 | Whale Riders: The Card Game | 0.604 | yes |
2021 | 315937 | X-Men: Mutant Insurrection | 0.601 | no |
2021 | 297129 | Jekyll vs. Hyde | 0.574 | yes |
2021 | 333553 | For the King (and Me) | 0.557 | no |
2021 | 324856 | The Crew: Mission Deep Sea | 0.549 | no |
2021 | 275044 | Glow | 0.536 | yes |
2021 | 290236 | Canvas | 0.530 | no |
2022 | 356033 | Libertalia: Winds of Galecrest | 0.519 | no |
2021 | 337389 | Snakesss | 0.514 | no |
2022 | 335764 | Unmatched: Battle of Legends, Volume Two | 0.510 | no |
2021 | 330174 | Explorers | 0.510 | yes |
2021 | 340237 | Wonder Book | 0.499 | no |
2021 | 316343 | Capital Lux 2: Pocket | 0.493 | no |
2021 | 340466 | Unfathomable | 0.491 | no |
2021 | 331635 | Kameloot | 0.491 | no |
2021 | 342848 | World of Warcraft: Wrath of the Lich King | 0.489 | no |
2021 | 340677 | Bad Company | 0.480 | no |
2021 | 299255 | Vienna Connection | 0.460 | no |
2021 | 340834 | Gravwell: 2nd Edition | 0.455 | no |
2021 | 329529 | Magellan: Elcano | 0.454 | no |
2021 | 291859 | Riftforce | 0.446 | no |
2021 | 319899 | Decktective: Nightmare in the Mirror | 0.445 | no |
2021 | 329084 | Space Dragons | 0.442 | no |
2021 | 314491 | Meadow | 0.435 | no |
2021 | 331059 | Last Message | 0.433 | no |
2021 | 336382 | Marvel United: X-Men | 0.415 | no |
2021 | 316080 | KeyForge: Dark Tidings | 0.413 | no |
2021 | 339906 | The Hunger | 0.408 | no |
2021 | 304783 | Hadrian's Wall | 0.406 | no |
2021 | 306881 | Railroad Ink Challenge: Lush Green Edition | 0.404 | no |
2021 | 293835 | Oltréé | 0.401 | no |
2021 | 322014 | All-Star Draft | 0.394 | no |
2021 | 282776 | Tumble Town | 0.389 | no |
2021 | 312767 | Lizard Wizard | 0.388 | no |
2021 | 329465 | Red Rising | 0.385 | yes |
2021 | 330532 | Hashi | 0.383 | no |
2021 | 305761 | Whale Riders | 0.379 | yes |
2021 | 330401 | Dokojong | 0.379 | no |